Remove all use of OrderedDict

datashader/core.py

@@ -9,7 +9,6 @@
 import dask.dataframe as dd
 import dask.array as da
 from xarray import DataArray, Dataset
-from collections import OrderedDict
 
 from .utils import Dispatcher, ngjit, calc_res, calc_bbox, orient_array, \
     dshape_from_xarray_dataset
@@ -1304,7 +1303,7 @@ def _cols_to_keep(columns, glyph, agg):
     Return which columns from the supplied data source are kept as they are
     needed by the specified agg. Excludes any SpecialColumn.
     """
-    cols_to_keep = OrderedDict({col: False for col in columns})
+    cols_to_keep = dict({col: False for col in columns})
     for col in glyph.required_columns():
         cols_to_keep[col] = True
 

datashader/data_libraries/dask.py

@@ -1,6 +1,5 @@
 from __future__ import annotations
 
-from collections import OrderedDict
 import numpy as np
 import pandas as pd
 import dask
@@ -58,7 +57,7 @@ def shape_bounds_st_and_axis(df, canvas, glyph):
 
     x_axis = canvas.x_axis.compute_index(x_st, width)
     y_axis = canvas.y_axis.compute_index(y_st, height)
-    axis = OrderedDict([(glyph.x_label, x_axis), (glyph.y_label, y_axis)])
+    axis = dict([(glyph.x_label, x_axis), (glyph.y_label, y_axis)])
 
     return shape, bounds, st, axis
 

datashader/data_libraries/dask_xarray.py

@@ -1,4 +1,3 @@
-from collections import OrderedDict
 from datashader.compiler import compile_components
 from datashader.utils import Dispatcher
 from datashader.glyphs.quadmesh import (
@@ -50,7 +49,7 @@ def shape_bounds_st_and_axis(xr_ds, canvas, glyph):
 
     x_axis = canvas.x_axis.compute_index(x_st, width)
     y_axis = canvas.y_axis.compute_index(y_st, height)
-    axis = OrderedDict([(glyph.x_label, x_axis), (glyph.y_label, y_axis)])
+    axis = dict([(glyph.x_label, x_axis), (glyph.y_label, y_axis)])
 
     return shape, bounds, st, axis
 
@@ -99,7 +98,7 @@ def chunk(np_arr, *inds):
             )
             chunk_coords_list.append([coord_name, coords[coord_name][coord_slice]])
 
-        chunk_coords = OrderedDict(chunk_coords_list)
+        chunk_coords = dict(chunk_coords_list)
         chunk_ds = xr.DataArray(
             np_arr, coords=chunk_coords, dims=coord_dims, name=var_name
         ).to_dataset()
@@ -197,7 +196,7 @@ def chunk(np_arr, *inds):
             )
             chunk_coords_list.append([coord_name, coords[coord_name][coord_slice]])
 
-        chunk_coords = OrderedDict(chunk_coords_list)
+        chunk_coords = dict(chunk_coords_list)
         chunk_ds = xr.DataArray(
             np_arr, coords=chunk_coords, dims=coord_dims, name=var_name
         ).to_dataset()

datashader/data_libraries/pandas.py

@@ -7,7 +7,6 @@
 from datashader.glyphs.points import _PointLike, _GeometryLike
 from datashader.glyphs.area import _AreaToLineLike
 from datashader.utils import Dispatcher
-from collections import OrderedDict
 
 __all__ = ()
 
@@ -49,7 +48,7 @@ def default(glyph, source, schema, canvas, summary, *, antialias=False, cuda=Fal
 
     return finalize(bases,
                     cuda=cuda,
-                    coords=OrderedDict([(glyph.x_label, x_axis),
-                                        (glyph.y_label, y_axis)]),
+                    coords=dict([(glyph.x_label, x_axis),
+                                 (glyph.y_label, y_axis)]),
                     dims=[glyph.y_label, glyph.x_label],
                     attrs=dict(x_range=x_range, y_range=y_range))

datashader/mpl_ext.py

@@ -1,4 +1,3 @@
-from collections import OrderedDict
 import warnings
 
 from matplotlib.image import _ImageBase
@@ -32,7 +31,7 @@ def to_ds_image(binned, rgba):
         return tf.Image(
             uint8_to_uint32(rgba),
             dims=binned.dims[:-1],
-            coords=OrderedDict(
+            coords=dict(
                 [
                     (binned.dims[1], binned.coords[binned.dims[1]]),
                     (binned.dims[0], binned.coords[binned.dims[0]]),

datashader/tests/test_quadmesh.py

@@ -4,7 +4,6 @@
 import xarray as xr
 import datashader as ds
 import pytest
-from collections import OrderedDict
 
 import dask.array
 from datashader.tests.test_pandas import assert_eq_ndarray, assert_eq_xr
@@ -557,7 +556,7 @@ def test_curve_quadmesh_autorange(array_module):
          [2.,  2.,  nan, nan],
          [2.,  nan, nan, nan]]
         ),
-        coords=OrderedDict([
+        coords=dict([
             ('Qx', x_coords),
             ('Qy', y_coords)]),
         dims=['Qy', 'Qx']
@@ -606,7 +605,7 @@ def test_curve_quadmesh_autorange_chunked():
          [2.,  2.,  nan, nan],
          [2.,  nan, nan, nan]]
         ),
-        coords=OrderedDict([
+        coords=dict([
             ('Qx', x_coords),
             ('Qy', y_coords)]),
         dims=['Qy', 'Qx']
@@ -657,7 +656,7 @@ def test_curve_quadmesh_manual_range(array_module):
          [2., 2., 3., 3.],
          [2., 2., 3., 3.]]
         ),
-        coords=OrderedDict([
+        coords=dict([
             ('Qx', x_coords),
             ('Qy', y_coords)]),
         dims=['Qy', 'Qx']
@@ -706,7 +705,7 @@ def test_curve_quadmesh_manual_range_subpixel(array_module):
          [nan, nan, nan],
          [nan, nan, nan]]
         ),
-        coords=OrderedDict([
+        coords=dict([
             ('Qx', x_coords),
             ('Qy', y_coords)]),
         dims=['Qy', 'Qx']

datashader/tests/test_transfer_functions.py

@@ -7,11 +7,10 @@
 import dask.array as da
 import PIL
 import pytest
-from collections import OrderedDict
 import datashader.transfer_functions as tf
 from datashader.tests.test_pandas import assert_eq_ndarray, assert_eq_xr
 
-coords = OrderedDict([('x_axis', [3, 4, 5]), ('y_axis', [0, 1, 2])])
+coords = dict([('x_axis', [3, 4, 5]), ('y_axis', [0, 1, 2])])
 dims = ['y_axis', 'x_axis']
 
 # CPU

datashader/transfer_functions/__init__.py

@@ -2,7 +2,6 @@
 
 from collections.abc import Iterator
 
-from collections import OrderedDict
 from io import BytesIO
 
 import warnings
@@ -356,7 +355,7 @@ def _colorize(agg, color_key, how, alpha, span, min_alpha, name, color_baseline,
     cats = agg.indexes[agg.dims[-1]]
     if not len(cats): # No categories and therefore no data; return an empty image
         return Image(np.zeros(agg.shape[0:2], dtype=np.uint32), dims=agg.dims[:-1],
-                     coords=OrderedDict([
+                     coords=dict([
                          (agg.dims[1], agg.coords[agg.dims[1]]),
                          (agg.dims[0], agg.coords[agg.dims[0]]) ]), name=name)
 
@@ -427,7 +426,7 @@ def _colorize(agg, color_key, how, alpha, span, min_alpha, name, color_baseline,
 
     return Image(values,
                  dims=agg.dims[:-1],
-                 coords=OrderedDict([
+                 coords=dict([
                      (agg.dims[1], agg.coords[agg.dims[1]]),
                      (agg.dims[0], agg.coords[agg.dims[0]]),
                  ]),

examples/filetimes.py

@@ -23,7 +23,6 @@
 
 from datashader.utils import export_image
 from datashader import transfer_functions as tf
-from collections import OrderedDict as odict
 
 #from multiprocessing.pool import ThreadPool
 #dask.set_options(pool=ThreadPool(3)) # select a pecific number of threads
@@ -51,7 +50,7 @@ class Parameters(object):
 filetypes_storing_categories = {'parq'}
 
 
-class Kwargs(odict):
+class Kwargs(dict):
     """Used to distinguish between dictionary argument values, and
     keyword-arguments.
     """
@@ -82,7 +81,7 @@ def benchmark(fn, args, filetype=None):
     # If we're loading data
     if filetype is not None:
         if filetype not in filetypes_storing_categories:
-            opts=odict()
+            opts = dict()
             if p.dftype == 'pandas':
                 opts['copy']=False
             for c in p.categories:
@@ -107,7 +106,7 @@ def benchmark(fn, args, filetype=None):
 
 
 
-read = odict([(f,odict()) for f in ["parq","snappy.parq","gz.parq","feather","h5","csv"]])
+read = dict([(f, dict()) for f in ["parq","snappy.parq","gz.parq","feather","h5","csv"]])
 
 def read_csv_dask(filepath, usecols=None):
     # Pandas writes CSV files out as a single file
@@ -143,7 +142,7 @@ def read_parq_pandas(filepath):
 read["snappy.parq"] ["pandas"] = lambda filepath,p,filetype:  benchmark(read_parq_pandas, (filepath,), filetype)
 
 
-write = odict([(f,odict()) for f in ["parq","snappy.parq","gz.parq","feather","h5","csv"]])
+write = dict([(f, dict()) for f in ["parq","snappy.parq","gz.parq","feather","h5","csv"]])
 
 write["csv"]          ["dask"]   = lambda df,filepath,p:  benchmark(df.to_csv, (filepath.replace(".csv","*.csv"), Kwargs(index=False)))
 write["h5"]           ["dask"]   = lambda df,filepath,p:  benchmark(df.to_hdf, (filepath, p.base))

examples/getting_started/2_Pipeline.ipynb

@@ -33,15 +33,14 @@
    "source": [
     "import pandas as pd\n",
     "import numpy as np\n",
-    "from collections import OrderedDict as odict\n",
     "\n",
     "num=10000\n",
     "np.random.seed(1)\n",
     "\n",
-    "dists = {cat: pd.DataFrame(odict([('x',np.random.normal(x,s,num)), \n",
-    "                                  ('y',np.random.normal(y,s,num)), \n",
-    "                                  ('val',val), \n",
-    "                                  ('cat',cat)]))      \n",
+    "dists = {cat: pd.DataFrame(dict([('x',np.random.normal(x,s,num)), \n",
+    "                                 ('y',np.random.normal(y,s,num)), \n",
+    "                                 ('val',val), \n",
+    "                                 ('cat',cat)]))      \n",
     "         for x,  y,  s,  val, cat in \n",
     "         [(  2,  2, 0.03, 10, \"d1\"), \n",
     "          (  2, -2, 0.10, 20, \"d2\"), \n",

examples/getting_started/3_Interactivity.ipynb

@@ -55,15 +55,14 @@
     "import numpy as np\n",
     "import datashader as ds\n",
     "import datashader.transfer_functions as tf\n",
-    "from collections import OrderedDict as odict\n",
     "\n",
     "num=100000\n",
     "np.random.seed(1)\n",
     "\n",
-    "dists = {cat: pd.DataFrame(odict([('x',np.random.normal(x,s,num)), \n",
-    "                                  ('y',np.random.normal(y,s,num)), \n",
-    "                                  ('val',val), \n",
-    "                                  ('cat',cat)]))      \n",
+    "dists = {cat: pd.DataFrame(dict([('x',np.random.normal(x,s,num)), \n",
+    "                                 ('y',np.random.normal(y,s,num)), \n",
+    "                                 ('val',val), \n",
+    "                                 ('cat',cat)]))      \n",
     "         for x,  y,  s,  val, cat in \n",
     "         [(  2,  2, 0.03, 10, \"d1\"), \n",
     "          (  2, -2, 0.10, 20, \"d2\"), \n",

examples/user_guide/3_Timeseries.ipynb

@@ -20,8 +20,7 @@
     "import numpy as np\n",
     "import xarray as xr\n",
     "import datashader as ds\n",
-    "import datashader.transfer_functions as tf\n",
-    "from collections import OrderedDict"
+    "import datashader.transfer_functions as tf"
    ]
   },
   {
@@ -121,7 +120,7 @@
    "source": [
     "%%time\n",
     "cvs = ds.Canvas(x_range=x_range, y_range=y_range, plot_height=300, plot_width=900)\n",
-    "aggs= OrderedDict((c, cvs.line(df, 'ITime', c)) for c in cols)\n",
+    "aggs= dict((c, cvs.line(df, 'ITime', c)) for c in cols)\n",
     "img = tf.shade(aggs['a'])"
    ]
   },